{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2 CUDA devices found, CUDA version 8.0\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "\u001b[32mimport \u001b[39m\u001b[36m$exec.$                          \n",
       "\u001b[39m\n",
       "\u001b[36mres0_1\u001b[39m: \u001b[32mAny\u001b[39m = (0.9634176,12314476544,12782075904)"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import $exec.^.lib.bidmach_notebook_init\n",
    "if (Mat.hasCUDA > 0) GPUmem"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot(sin(row(0->1000)*0.01))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": "text/x-scala",
   "file_extension": ".scala",
   "mimetype": "text/x-scala",
   "name": "scala211",
   "nbconvert_exporter": "script",
   "pygments_lexer": "scala",
   "version": "2.11.11"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}
